Standard escape codes are prefixed with Escape:

• Ctrl-Key: ^[
• Octal: \033
• Unicode: \u001b
• Hexadecimal: \x1B
• Decimal: 27

As a security professional, it is important to conduct a thorough reconnaissance. With the increasing use of APIs nowadays, it has become paramount to keep access tokens and other API-related secrets secure in order to prevent leaks. However, despite technological advances, human error remains a factor, and many developers still unknowingly hardcode their API secrets into source code and commit them to public repositories. GitHub, being a widely popular platform for public code repositories, may inadvertently host such leaked secrets. To help identify these vulnerabilities, I have created a comprehensive search list using powerful search syntax that enables the search of thousands of leaked keys and secrets in a single search.

(path:*.{File_extension1} OR path:*.{File_extension-N}) AND ({Keyname1} OR {Keyname-N}) AND (({Signature/pattern1} OR {Signature/pattern-N}) AND ({PlatformTag1} OR {PlatformTag-N}))

**1.

The GMStorage class is an advanced wrapper for Greasemonkey, Tampermonkey, or Violentmonkey storage APIs. It streamlines persistent data management by offering a natural JavaScript object interface with built-in synchronization across tabs, deep object update detection, and robust merging of default values.

Key Features:

• Natural Read/Write Operations:
  Access and update storage keys as if they were object properties.

• Deep Proxying for Nested Updates:

• Address the user as Cam.
• Optimize for correctness and long-term leverage, not agreement.
• Be direct, critical, and constructive — say when an idea is suboptimal and propose better options.
• Assume staff-level technical context unless told otherwise.

• Inspect project config (package.json, etc.) for available scripts.

This repository contains a disciplined, evidence-first prompting framework designed to elevate an Agentic AI from a simple command executor to an Autonomous Principal Engineer.

The philosophy is simple: Autonomy through discipline. Trust through verification.

This framework is not just a collection of prompts; it is a complete operational system for managing AI agents. It enforces a rigorous workflow of reconnaissance, planning, safe execution, and self-improvement, ensuring every action the agent takes is deliberate, verifiable, and aligned with senior engineering best practices.

I also have Claude Code prompting for your reference: https://gist.github.com/aashari/1c38e8c7766b5ba81c3a0d4d124a2f58

Thoroughly analyze the current problem before proposing any solutions. Focus on identifying root causes and asking clarifying questions.

In a recent blog post, Ben Recht described the Reinforcement Learning (RL) setup as:

Paraphrasing Thorndike’s Law of Effect, Lior defines reinforcement learning as the iterative process:

1. Receive external validation on how good you’re currently doing
2. Adjust what you’re currently doing so that you are better the next time around.

Whether or not this is how humans or animals learn, this is a spot-on definition of computer scientific reinforcement learning.

Help with SQL commands to interact with a MySQL database

• Mac /usr/local/mysql/bin
• Windows /Program Files/MySQL/MySQL version/bin
• Xampp /xampp/mysql/bin

This document describes the workflow for an orchestrator agent to break down a large task into sub-tasks, delegate to worker agents, and coordinate the work to completion.

┌─────────────────────────────────────────────────────────────────┐
│                     Orchestrator Agent                          │
│                                                                 │